Benchmarking Domain Intelligence
Large language models are improving rapidly; to date, this improvement has largely been measured via academic benchmarks. These benchmarks, such as MMLU and...
Page 1
The Long Context RAG Capabilities of OpenAI o1 and Google Gemini
Retrieval Augmented Generation (RAG) is the top use case for Databricks customers who want to customize AI workflows on their own data. The...
Beyond the Leaderboard: Unpacking Function Calling Evaluation
1. Introduction The research and engineering community at large have been continuously iterating upon Large Language Models (LLMs) in order to make them...
Long Context RAG Performance of LLMs
Retrieval Augmented Generation (RAG) is the most widely adopted generative AI use case among our customers. RAG enhances the accuracy of LLMs by...
Introducing Llama2-70B-Chat with MosaicML Inference
Llama2-70B-Chat is a leading AI model for text completion, comparable with ChatGPT in terms of quality. Today, organizations can leverage this state-of-the-art model...
Announcing MPT-7B-8K: 8K Context Length for Document Understanding
Today, we are releasing MPT-7B-8K, a 7B parameter open-source LLM with 8k context length trained with the MosaicML platform. MPT-7B-8K was pretrained starting...
MosaicBERT: Pretraining BERT from Scratch for $20
With the MosaicBERT architecture + training recipe, you can now pretrain a competitive BERT-Base model from scratch on the MosaicML platform for $20...
MosaicML Delivers Leading NLP Performance in MLPerf v2.1
MosaicML leads the MLPerf NLP results, delivering a score of 7.9 minutes on 8x NVIDIA A100 GPUs in the Open Division, thanks to...